Computer-aided diagnosis of atrial fibrillation based on ECG Signals: A review

Y Hagiwara, H Fujita, SL Oh, JH Tan, R San Tan… - Information …, 2018 - Elsevier
Arrhythmia is a type of disorder that affects the pattern and rate of the heartbeat. Among the
various arrhythmia conditions, atrial fibrillation (AF) is the most prevalent. AF is associated …

AF classification from a short single lead ECG recording: The PhysioNet/computing in cardiology challenge 2017

GD Clifford, C Liu, B Moody, HL Li-wei… - 2017 Computing in …, 2017 - ieeexplore.ieee.org
The PhysioNet/Computing in Cardiology (CinC) Challenge 2017 focused on differentiating
AF from noise, normal or other rhythms in short term (from 9-61 s) ECG recordings …

A review of atrial fibrillation detection methods as a service

O Faust, EJ Ciaccio, UR Acharya - International journal of environmental …, 2020 - mdpi.com
Atrial Fibrillation (AF) is a common heart arrhythmia that often goes undetected, and even if it
is detected, managing the condition may be challenging. In this paper, we review how the …

ECG signal classification for the detection of cardiac arrhythmias using a convolutional recurrent neural network

Z **ong, MP Nash, E Cheng, VV Fedorov… - Physiological …, 2018 - iopscience.iop.org
Objective: The electrocardiogram (ECG) provides an effective, non-invasive approach for
clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the …

Inferior myocardial infarction detection using stationary wavelet transform and machine learning approach

LD Sharma, RK Sunkaria - Signal, Image and Video Processing, 2018 - Springer
Early and accurate detection of myocardial infarction is imperative for reducing the mortality
rate due to heart attack. Present work proposes a novel technique aiming toward accurate …

Automatic detection of atrial fibrillation based on continuous wavelet transform and 2D convolutional neural networks

R He, K Wang, N Zhao, Y Liu, Y Yuan, Q Li… - Frontiers in …, 2018 - frontiersin.org
Atrial fibrillation (AF) is the most common cardiac arrhythmias causing morbidity and
mortality. AF may appear as episodes of very short (ie, proximal AF) or sustained duration …

Multiple sclerosis detection based on biorthogonal wavelet transform, RBF kernel principal component analysis, and logistic regression

SH Wang, TM Zhan, Y Chen, Y Zhang, M Yang… - IEEE …, 2016 - ieeexplore.ieee.org
To detect multiple sclerosis (MS) diseases early, we proposed a novel method on the
hardware of magnetic resonance imaging, and on the software of three successful methods …

Integration of results from convolutional neural network in a support vector machine for the detection of atrial fibrillation

C Ma, S Wei, T Chen, J Zhong, Z Liu… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Atrial fibrillation (AF) can cause a variety of heart diseases and its detection is insufficient in
outside hospital. We proposed three methods for AF diagnosis in ambulatory settings. The …

MINA: multilevel knowledge-guided attention for modeling electrocardiography signals

S Hong, C **ao, T Ma, H Li, J Sun - arxiv preprint arxiv:1905.11333, 2019 - arxiv.org
Electrocardiography (ECG) signals are commonly used to diagnose various cardiac
abnormalities. Recently, deep learning models showed initial success on modeling ECG …

A novel interpretable method based on dual-level attentional deep neural network for actual multilabel arrhythmia detection

Y **, J Liu, Y Liu, C Qin, Z Li, D **ao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Arrhythmia accounts for more than 80% of sudden cardiac death, and its incidence rate has
increased rapidly recently. Nowadays, many studies have applied artificial intelligence (AI) …